CN113127807A - Mode5 leading pulse jitter value calculation method and system based on constrained least square algorithm - Google Patents
Mode5 leading pulse jitter value calculation method and system based on constrained least square algorithm Download PDFInfo
- Publication number
- CN113127807A CN113127807A CN202110418588.2A CN202110418588A CN113127807A CN 113127807 A CN113127807 A CN 113127807A CN 202110418588 A CN202110418588 A CN 202110418588A CN 113127807 A CN113127807 A CN 113127807A
- Authority
- CN
- China
- Prior art keywords
- mode5
- pulse
- signal
- jitter value
- constrained
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000004422 calculation algorithm Methods 0.000 title claims abstract description 46
- 238000004364 calculation method Methods 0.000 title claims description 23
- 238000000034 method Methods 0.000 claims abstract description 25
- 238000005070 sampling Methods 0.000 claims abstract description 22
- 230000001360 synchronised effect Effects 0.000 claims abstract description 18
- 238000001228 spectrum Methods 0.000 claims abstract description 17
- 238000001514 detection method Methods 0.000 claims abstract description 14
- 238000005259 measurement Methods 0.000 claims abstract description 8
- 230000004044 response Effects 0.000 claims description 24
- 238000012545 processing Methods 0.000 claims description 9
- 230000001629 suppression Effects 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 230000007613 environmental effect Effects 0.000 claims description 4
- 238000004891 communication Methods 0.000 claims description 3
- 238000009795 derivation Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 abstract description 3
- 230000006870 function Effects 0.000 description 7
- 238000004458 analytical method Methods 0.000 description 5
- 230000003750 conditioning effect Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 230000005855 radiation Effects 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 238000007796 conventional method Methods 0.000 description 3
- 239000013598 vector Substances 0.000 description 3
- 238000007476 Maximum Likelihood Methods 0.000 description 2
- 238000013459 approach Methods 0.000 description 2
- 231100000518 lethal Toxicity 0.000 description 2
- 230000001665 lethal effect Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 101100458289 Drosophila melanogaster msps gene Proteins 0.000 description 1
- 238000000342 Monte Carlo simulation Methods 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000005314 correlation function Methods 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/141—Discrete Fourier transforms
- G06F17/142—Fast Fourier transforms, e.g. using a Cooley-Tukey type algorithm
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/12—Classification; Matching
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Analysis (AREA)
- Theoretical Computer Science (AREA)
- Pure & Applied Mathematics (AREA)
- Computational Mathematics (AREA)
- Mathematical Optimization (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Discrete Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Operations Research (AREA)
- Probability & Statistics with Applications (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention discloses a method and a system for calculating a jitter value of a Mode5 leading pulse based on a constrained least square algorithm. Specifically, the IFF signal is sampled in real time to obtain original sampling data and synchronized sliding delay. And performing frequency domain signal detection and time domain parameter measurement on the original sampling data to obtain pulse train information, and judging whether the signal is a Mode5 signal by using a tree structure. If the judgment is successful, performing accurate time delay on the original sampling data, and performing FFT on the data subjected to synchronous sliding time delay and accurate time delay respectively to obtain a complex result; and performing conjugate multiplication on complex results to obtain a cross-correlation spectrum, calculating the arc tangent of the cross-correlation spectrum by using a CORDIC algorithm, performing phase ambiguity resolution on the arc tangent result in a system detection range, and performing linear fitting on the processed result by using an RLS algorithm to obtain a leading pulse jitter value of the Mode5 signal. The calculated leading pulse jitter value has high precision and good robustness, can support the signal individual identification technology, and meets the reconnaissance requirement of the friend or foe identification equipment at the present stage.
Description
Technical Field
The invention relates to the field of information reconnaissance in electronic countermeasure, in particular to a method and a system for calculating a jitter value of a Mode5 leading pulse based on a constrained least square algorithm.
Background
The Mark XIIA friend or foe identification system is an upgraded version of Mark XII, and a Mode5 is added on the basis of the original system. The Mode5 system adopts a safe information format and a data transmission technology, improves the safety, anti-interference performance and battlefield situation perception capability of the system, and can be used for fighting identification of air-to-ground, ground-to-air, air-to-air, sea-to-sea and the like. Currently, military monitoring platforms of American military and North American military, such as E-3B AWACS, E-2C early warning machines and Yusi shield combat systems are all equipped with a Mode5 system, and IFF systems of other air, ground and water surface combat platforms are gradually upgraded to a Mode5 system.
The Mode5 system is typically characterized by having a leading pulse with cryptographic information and jitter vector characteristics, and a high degree of computation of its jitter value is critical to the fine feature analysis of friend or foe identification equipment. The index can directly assess the clock stability, the circuit unintentional modulation characteristic and the like of the radiation source transmitter baseband conditioning circuit, and has important significance as target fine analysis and even fingerprint analysis.
At present, although different individual identification devices for friend or foe have stable jitter value parameters issued by an encryption machine within a certain period of time, if the jitter value parameters can be measured with high precision, the corresponding jitter values of the individual identification devices for friend or foe are found to be different. The difference is mainly determined by a baseband conditioning circuit in the transmitter, the baseband conditioning circuit comprises a baseband data generating unit, a baseband clock control unit, an up-conversion radio frequency unit and the like, intentional and unintentional modulation generated in the signal generating process causes a plurality of unique feature vectors of the device, just like human fingerprints, and a leading pulse jitter value is one of the unique feature vectors.
For the measurement of the jitter value of the leading pulse, when the in-band signal-to-noise ratio is below 10dB, the conventional method uses the single pulse arrival time (ToA) to perform differential calculation, the root mean square error of the jitter value is large, and the requirement of the individual identification field of the existing stage friend or foe identification equipment cannot be met.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method and a system for calculating a Mode5 leading pulse jitter value based on a constrained least square algorithm, accurately calculating the time difference between pulse signals through linear fitting of the algorithm, and further accurately calculating the leading pulse jitter value of the current Mode5 signal.
A method for calculating a jitter value of a Mode5 preamble pulse based on a constrained least square algorithm comprises the following steps:
1) acquiring AD (analog-to-digital) to sample IFF signals in real time to obtain original sampling data, and performing synchronous sliding time delay on the original sampling data in real time in an FPGA (field programmable gate array);
2) original sampling data is transformed to a frequency domain through FFT operation, and then time-frequency domain guide information of rough measurement is obtained through CFAR, environmental noise bottom detection and communication signal self-adaptive suppression; after the roughly measured time-frequency domain guide information is subjected to down-conversion, accurate parameter measurement is carried out in a time domain to obtain pulse train information;
3) the pulse train information comprehensively judges whether the current signal is a Mode5 signal or not in an effective time window through a tree structure; if the signal is a Mode5 signal, carrying out accurate time delay on original sampling data, and respectively carrying out synchronous pipelined FFT on the synchronous sliding time delay and the original sampling data after the accurate time delay to obtain a complex result; conjugate multiplying the complex result point by point to obtain cross correlation spectrum, and detecting the cross correlation spectrum; if the signal is a non-Mode 5 signal, discarding the cache data and not calculating any more;
4) calculating an arc tangent result of the cross-correlation spectrum in real time by using a CORDIC algorithm, then presetting a sliding window, a detection time window and the maximum and minimum ranges of an arc tangent calculation angle according to a base line position, and performing phase ambiguity resolution on the arc tangent result in a system detection range to obtain a phase ambiguity resolution processing result;
5) the phase solution fuzzy processing result is subjected to linear fitting of a constrained least square algorithm to obtain a first-order coefficient of the time difference estimation variance;
6) and calculating the time difference value of the Mode5 signal in real time according to the first-order coefficient of the time difference estimation variance, wherein the time difference value is the jitter value of the leading pulse of the current Mode5 signal.
Further, the IFF signal of @140MHz intermediate frequency is sampled in real time by collecting 200MspsAD in the step 1).
Further, the burst information in step 2) includes a burst first pulse arrival time ToA, a pulse frequency Freq, a pulse amplitude Amp, each pulse width PW, a real-time initial Phase, and a pulse modulation type MoP.
Further, in the step 3), synchronous stream-wise FFT is respectively performed on the original sampling data after synchronous sliding delay and accurate delay, and the number of FFT points is 256.
Further, the step 5) specifically comprises:
A1. the phase ambiguity resolution processing result comprises a phase, and derivation calculation is carried out on discrete data of the phase, wherein the discrete form of the phase is as follows:
φ(ωi)=-ωiD+εi,i=0,1,…,M+1
m is the number of FFT points and an interference term epsiloniIs a random variable, phi (omega)i) Is the phase, ωiThe data are phase discrete data, and D is time difference;
A2. let the cost function of the constrained least squares algorithm be
Time difference estimation to calculate time difference DTime difference estimationIs calculated by the formula
In the ideal noise-free case, i is 0, phi (ω)i)=0,For unbiased estimation, instantaneous difference estimationHas a mean value of
Further, the step 6) specifically includes: and according to the first-order coefficient, pulse-by-pulse time difference calculation is carried out on the Mode5 signal by adopting a phase data time difference estimation method, so as to obtain the time difference value of the Mode5 signal, wherein the time difference value is the jitter value of the leading pulse of the Mode5 signal.
Further, when the cross-correlation spectrum is detected in the step 3), an initial threshold of the cross-correlation spectrum detection is preset or issued in real time according to the current signal environment.
A Mode5 leading pulse jitter value calculation system based on a constraint least square algorithm is a Mode5 system, and the Mode5 system calculates the leading pulse jitter value of a Mode5 signal through the constraint least square algorithm;
the Mode5 system has 4-level working modes, including: a Level1 working mode, a Level2 working mode, a Level3 working mode and a Level4 working mode;
the Level1 operation mode is an improved inquiry/response identification mode;
the Level2 working mode is a situation awareness identification mode with a GPS position report;
the Level3 working mode is an friend target address selection inquiry mode;
the Level4 working mode is a data transmission mode.
Further, the Mode5 system comprises a query format and a response format; the response formats comprise a Level1 response format and a Level2 response format, the response format receives response signals, and the inquiry format receives inquiry signals;
the interrogation signal received by the interrogation format comprises 4 synchronization pulses, 2 sidelobe suppression pulses and 11 data pulses, and the effective pulse width of each pulse is 1 mu s;
the response signal received by the Level1 response format comprises 2 synchronous pulses and 1 data long pulse;
the reply signal received by the Level2 reply format comprises 4 synchronization pulses and 1 data length pulse.
The invention has the beneficial effects that: the invention can measure the jitter value of the signal leading pulse with low cost and high performance 200Msps AD, the precision of the jitter value can reach 1.3ns (RMS) (SNR is better than 12dB), the SNR is far better than that of the conventional measuring method, and the calculation variance can reach CRLB. The invention is particularly suitable for being realized by using FPGA real-time flow in engineering application, and has the advantages of stable operation, high data throughput rate and larger processing bandwidth. Through the verification of actual equipment, the invention meets the precondition requirement of individual identification of the radiation source in the complex electromagnetic environment of an external field.
Drawings
Fig. 1 is an algorithm flowchart of a Mode5 preamble pulse jitter value calculation method based on a constrained least square algorithm according to the present invention.
FIG. 2 is a query format diagram of a Mode5 preamble jitter value calculation system based on a constrained least squares algorithm according to the present invention.
FIG. 3 is a Level1 response format diagram of a Mode5 preamble pulse jitter value calculation system based on a constrained least square algorithm.
FIG. 4 is a diagram of a system Level2 response format for calculating jitter values of Mode5 preamble pulses based on a constrained least squares algorithm.
Fig. 5 is a simulation diagram of the effect achieved in the calculation method of the jitter value of the Mode5 preamble pulse based on the constrained least square algorithm.
Detailed Description
The specific steps of the time difference calculation of the Mode5 leading pulse jitter value calculation method based on the constrained least square algorithm are shown in fig. 1:
1) acquiring AD (analog-to-digital) to sample IFF signals in real time to obtain original sampling data, and performing synchronous sliding time delay on the original sampling data in real time in an FPGA (field programmable gate array); acquisition AD the IFF signal at the intermediate frequency of @140MHz is sampled in real time, preferably by 200 MspsAD.
2) Original sampling data is transformed to a frequency domain through FFT operation, and then is subjected to CFAR, environmental noise bottom detection and communication signal adaptive suppression to obtain time-frequency domain guide information of rough detection; after the roughly measured time-frequency domain guide information is subjected to down-conversion, accurate parameter measurement is carried out in a time domain to obtain pulse train information; the burst information includes a burst head pulse arrival time ToA, a pulse frequency Freq, a pulse amplitude Amp, each pulse width PW, a real-time initial Phase, a pulse modulation type MoP, and the like.
3) The pulse train information comprehensively judges whether the current signal is a Mode5 signal or not in an effective time window through a tree structure; if the signal is a Mode5 signal, carrying out accurate time delay on original sampling data, and respectively carrying out synchronous pipelined FFT on the synchronous sliding time delay and the original sampling data after the accurate time delay to obtain a complex result; conjugate multiplying the complex result point by point to obtain cross correlation spectrum, and detecting the cross correlation spectrum; if the signal is a non-Mode 5 signal, discarding the cache data and not operating any more so as to save the operation resources;
4) calculating an arc tangent result of the cross-correlation spectrum in real time by using a CORDIC algorithm, then presetting a sliding window, a detection time window and the maximum and minimum ranges of an arc tangent calculation angle according to a base line position, and performing phase ambiguity resolution on the arc tangent result in a system detection range to obtain a phase ambiguity resolution processing result;
5) the phase solution fuzzy processing result is subjected to linear fitting of a constrained least square algorithm to obtain a first-order coefficient of the time difference estimation variance;
6) and calculating the time difference value of the Mode5 signal in real time according to the first-order coefficient of the time difference estimation variance, wherein the time difference value is the jitter value of the leading pulse of the current Mode5 signal. The invention preferably uses phase data time difference estimation to calculate the pulse-by-pulse time difference of the Mode5 signal.
The principle of the constrained least square algorithm of the invention is as follows:
since the cross-correlation function of the signals x (t) and y (t) is defined as
Gxy(ω)=X(ω)Y*(ω)=Gs(ω)e-jωD
Therefore, the time difference information is contained in the cross-correlation spectrum function GxyOf the phases of (ω), i.e., the phase Φ (ω) ═ ω D, due to the presence of noise
φ(ω)=-ωD+ε
Wherein, operators Im and Re represent the imaginary part and the real part of the equation respectively.
The discrete form of the phase is shown below
φ(ωi)=-ωiD+εi,i=0,1,…,M+1
M is the number of FFT points, and 256 points are preferred in the model 5 system to be compatible with different modes. Interference term epsiloniIs a random variable, resulting in a phase phi (omega)i) Deviation of (e ∈)iMixed noise n mainly influenced by thermal noise, environmental noise, etc. of receiverx(t)、ny(t) and the number of finite observation points.
For the derivation of the discrete data of the above formula, a linear fitting mode can be adopted in engineering to save the operation amount and approach the required precision according to the engineering requirement.
Least Squares (LS) algorithms are commonly used in engineering to achieve linear fitting. The cost function of LS is
J=∑(φ(ωi)+ωiD)2=∑εi 2
then, a phase weighting function is usedIn the frequency domain against the phase function phi (omega)i) Weighting is performed to form an LS-based time difference estimation method.
However, this algorithm requires a large statistical a priori knowledge of the signal and noise and is only suitable for the case of noise-free interference or uncorrelated gaussian noise interference. This is hardly achievable for electronic reconnaissance systems.
Based on the method, the linear fitting is realized by selecting the constraint least square, and the cost of the least square algorithm is modified to be
Time difference estimation to calculate time difference DTime difference estimationThe calculation formula of (2) is as follows:
compared with the LS-based time difference estimation method, the above formula contains the concept of RLS, and RLS fully utilizes the prior information that the intercept of the fitted straight line is zero.
I.e. in the ideal noise-free case, i is 0, phi (ω)i) 0, which is substantially equivalent to a Maximum Likelihood (ML) estimation, the variance calculated by the RLS-based moveout estimation method is smaller than the variance calculated by the LS-based moveout estimation method. According to the formula, the compound can be obtained,for unbiased estimation, instantaneous difference estimationMean value ofThe variance is:
wherein epsiloniApproximately Gaussian distribution, with mean of zero and variance of
K is a constant related to the number of stages L, the degree of overlap K, etc., and is used to calculate Gxy(omega) estimation
Since the FFT has a finite length in actual calculation, the signals x (t) and y (t) are divided into L segments, each segment having M points, with an overlap of κ. FFT is carried out on each segment of data, then cross correlation is solved, and G can be obtainedxyThe formula of (omega) is
Wherein, Xl(omega) and Yl(ω) FFT complex results for the first segment of data, x (t) and y (t), respectively. All have E [ epsilon ]i 2]=σiCan be obtained by substituting the above formula
This is in conjunction with
Is consistent, is a discrete form thereof. Wherein
T is the number of data points.
The variance of the RLS-based time difference estimation method can reach CRLB.
Based on the precision, the method for calculating the jitter value of the Mode5 leading pulse of the constrained least square algorithm is applied to an identification and reconnaissance processing system of the enemy and has strong requirements in the application of individual identification of the target of the radiation source.
The invention provides a system for calculating a jitter value of a Mode5 preamble pulse based on a constrained least square algorithm, which is a Mode5 system, and a Mode5 system calculates the jitter value of the preamble pulse of a Mode5 signal by the constrained least square algorithm. The background signal for the Mode5 system is the north model 5 IFF signal, and the specific signal format is as follows:
the Mode5 system has 4-Level working Mode, Level1 working Mode, Level2 working Mode, Level3 working Mode and Level4 working Mode. The Level1 working mode is an improved inquiry/response identification mode, a platform identification number and a lethal factor are added, and the lethal factor is destructive inquiry information with a command attack intention; the Level2 working mode is a situational knowledge distinguishing mode with a GPS position report and comprises information such as longitude and latitude, height, country codes, task codes and the like; the Level3 working mode is an friend target site selection inquiry mode, and individual inquiry on a specific platform in a friend party battle group, such as a flagship of a naval fleet and a long airplane of a flying team is realized; the Level4 working mode is a data transmission mode, and can realize high-capacity and high-speed data transmission and exchange among various weapon platforms such as air, water surface and ground.
The model 5 system comprises a query format and a response format; the answer formats include a Level1 answer format for receiving answer signals and a Level2 answer format for receiving inquiry signals.
As shown in fig. 2, the interrogation signal of the interrogation format includes 4 synchronization pulses P1 to P4, 2 sidelobe suppression pulses L1 to L2, and 11 data pulses D1 to D11, and has an effective pulse width of 1 μ s. The variation of the sync pulse interval is S1-S3, which is determined by the 8-bit data provided by the encryption machine. The signal is modulated by a direct sequence spread spectrum MSK based on Walsh codes with the period of 16, and the code rate is 16 MBaud.
The Level1 response format is shown in FIG. 3. The Level1 answer format signal is composed of 2 synchronization pulses P1-P2 and 1 data long pulse D1-D9. The sync pulse has a pulse width of 1 mus and the long pulse lasts 9 mus. There are 16 cases of the P1 and P2 pulse intervals S1: 0-1.875 μ s in increments of 0.125 μ s. All pulses are MSK modulated at a code rate of 16 MBaud.
The Level2 response format is shown in FIG. 4. The Level2 reply format signal is composed of 4 synchronization pulses P1-P4 and 1 data long pulse D1-D33. The duration of the effective pulse width of the sync pulse is 1 mus and the duration of the data long pulse is 33 mus. The sync pulse interval is variable, and the variation is S1-S3, determined by the 8bit data provided by the encryption machine. The synchronization pulse and the long pulse are MSK modulated, and the code rate is 16 MBaud.
Although the encryption jitter values sent by the encryption machine are stable in a certain period of time, if the encryption jitter values are measured with high precision, the corresponding jitter values are different and are mainly determined by a baseband conditioning circuit in the transmitter, the baseband conditioning circuit comprises a baseband data generation unit, a baseband clock control unit, an up-conversion radio frequency unit and the like, the unintentional modulation generated in the operation process can be realized, and the Mode5 system can uniquely identify the enemy identification equipment individual just like a human fingerprint.
The specific implementation result of the invention is as follows:
in 1000 Monte Carlo experiments of the algorithm, the rising edge duration of a Mode5 signal pulse is set to be 100ns, the effective pulse width is set to be 1us, the falling edge duration is set to be 100ns, the intermediate frequency is set to be 140MHz, the signal-to-noise ratio is respectively set to be 0-31dB, and the sampling rate is set to be 200 Msps. The simulation results are shown in fig. 5.
In a simulation result diagram, a circular curve is a conventional method, and a calculation precision error curve is obtained by down-converting a single pulse signal to a baseband, calculating the arrival time (ToA) of the first pulse and calculating the difference; the triangular curve is the corresponding result of the present invention. As can be seen from simulation, when the in-band signal-to-noise ratio is below 10dB, the root mean square error of the jitter value is large, and far exceeds the algorithm of the Mode5 system, and the jitter value is in an unavailable state in corresponding engineering application. Along with the improvement of the signal-to-noise ratio, the precision of the two algorithms is gradually converged and gradually approaches to the CRLB.
Through engineering verification, when the Mode5 system carries out 200Msps sampling, the jitter value measurement accuracy of the leading pulse can reach 1.3ns (RMS) (the signal-to-noise ratio is better than 12dB), and the method is far better than the conventional method.
The engineering realization precision of the invention plays a key role in individual identification and fine feature analysis of friend or foe identification equipment, and the engineering precision can be achieved, and the requirements of the field at the present stage are also met. The method can stably calculate the leading pulse jitter value of the Mode5 signal, and lays a foundation for further fine feature analysis and individual identification of the radiation source.
It should be understood that the above-described embodiments are merely preferred embodiments of the present invention and the principles of the applied technology, and any changes, modifications, substitutions, combinations, and simplifications made by those skilled in the art without departing from the spirit and principle of the present invention shall be considered as equivalent replacements within the technical scope of the present invention.
Claims (9)
1. A Mode5 leading pulse jitter value calculation method based on a constraint least square algorithm is characterized in that: the method comprises the following steps:
1) acquiring AD (analog-to-digital) to sample IFF signals in real time to obtain original sampling data, and performing synchronous sliding time delay on the original sampling data in real time in an FPGA (field programmable gate array);
2) original sampling data is transformed to a frequency domain through FFT operation, and then time-frequency domain guide information of rough measurement is obtained through CFAR, environmental noise bottom detection and communication signal self-adaptive suppression; after the roughly measured time-frequency domain guide information is subjected to down-conversion, accurate parameter measurement is carried out in a time domain to obtain pulse train information;
3) the pulse train information comprehensively judges whether the current signal is a Mode5 signal or not in an effective time window through a tree structure; if the signal is a Mode5 signal, carrying out accurate time delay on original sampling data, and respectively carrying out synchronous pipelined FFT on the synchronous sliding time delay and the original sampling data after the accurate time delay to obtain a complex result; conjugate multiplying the complex result point by point to obtain cross correlation spectrum, and detecting the cross correlation spectrum; if the signal is a non-Mode 5 signal, discarding the cache data and not calculating any more;
4) calculating an arc tangent result of the cross-correlation spectrum in real time by using a CORDIC algorithm, then presetting a sliding window, a detection time window and the maximum and minimum ranges of an arc tangent calculation angle according to a base line position, and performing phase ambiguity resolution on the arc tangent result in a system detection range to obtain a phase ambiguity resolution result;
5) the phase solution fuzzy processing result is subjected to linear fitting of a constrained least square algorithm to obtain a first-order coefficient of the time difference estimation variance;
6) and calculating the time difference value of the Mode5 signal in real time according to the first-order coefficient of the time difference estimation variance, wherein the time difference value is the jitter value of the leading pulse of the current Mode5 signal.
2. The method for calculating the jitter value of the Mode5 preamble pulse based on the constrained least squares algorithm as claimed in claim 1, wherein: the IFF signal of @140MHz intermediate frequency is sampled in real time by collecting 200MspsAD in the step 1).
3. The method for calculating the jitter value of the Mode5 preamble pulse based on the constrained least squares algorithm as claimed in claim 1, wherein: the information of the pulse train in the step 2) comprises the arrival time ToA of the first pulse of the pulse train, the pulse frequency Freq, the pulse amplitude Amp, each pulse width PW, the real-time initial Phase and the pulse modulation type MoP.
4. The method for calculating the jitter value of the Mode5 preamble pulse based on the constrained least squares algorithm as claimed in claim 1, wherein: and in the step 3), synchronous flow FFT is respectively carried out on the original sampling data after synchronous sliding delay and accurate delay, and the number of FFT is 256.
5. The method for calculating the jitter value of the Mode5 preamble pulse based on the constrained least squares algorithm as claimed in claim 1, wherein: the step 5) is specifically as follows:
A1. the phase ambiguity resolution processing result comprises a phase, and derivation calculation is carried out on discrete data of the phase, wherein the discrete form of the phase is as follows:
φ(ωi)=-ωiD+εi,i=0,1,…,M+1
m is the number of FFT points and an interference term epsiloniIs a random variable, phi (omega)i) Is the phase, ωiD is time difference of discrete data of the phase;
A2. let the cost function of the constrained least squares algorithm be
Time difference estimation to calculate time difference DTime difference estimationIs calculated by the formula
In the ideal noise-free case, i is 0, phi (ω)i)=0,For unbiased estimation, instantaneous difference estimationHas a mean value of
6. The method for calculating the jitter value of the Mode5 preamble pulse based on the constrained least squares algorithm as claimed in claim 1, wherein: the step 6) is specifically as follows: and according to the first-order coefficient, pulse-by-pulse time difference calculation is carried out on the Mode5 signal by adopting a phase data time difference estimation method, so as to obtain the time difference value of the Mode5 signal, wherein the time difference value is the jitter value of the leading pulse of the Mode5 signal.
7. The method for calculating the jitter value of the Mode5 preamble pulse based on the constrained least squares algorithm as claimed in claim 1, wherein: when the cross-correlation spectrum is detected in the step 3), an initial threshold of the cross-correlation spectrum detection is preset or issued in real time according to the current signal environment.
8. A Mode5 leading pulse jitter value calculation system based on constraint least square algorithm is characterized in that: the system is a Mode5 system, and the Mode5 system calculates the jitter value of the leading pulse of the Mode5 signal by a constrained least square algorithm;
the Mode5 system has 4-level working modes, including: a Level1 working mode, a Level2 working mode, a Level3 working mode and a Level4 working mode;
the Level1 operation mode is an improved inquiry/response identification mode;
the Level2 working mode is a situation awareness identification mode with a GPS position report;
the Level3 working mode is an friend target address selection inquiry mode;
the Level4 working mode is a data transmission mode.
9. The system for calculating the jitter value of the Mode5 preamble pulse based on the constrained least squares algorithm of claim 8, wherein: the model 5 system comprises a query format and a response format; the response formats comprise a Level1 response format and a Level2 response format, the response formats receive response signals, and the inquiry formats receive inquiry signals;
the interrogation signal received by the interrogation format comprises 4 synchronization pulses, 2 sidelobe suppression pulses and 11 data pulses, and the effective pulse width of each pulse is 1 mu s;
the response signal received by the Level1 response format comprises 2 synchronous pulses and 1 data length pulse;
the reply signal received by the Level2 reply format comprises 4 synchronous pulses and 1 data length pulse.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110418588.2A CN113127807B (en) | 2021-04-19 | 2021-04-19 | Mode5 leading pulse jitter value calculation method based on constrained least square algorithm |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110418588.2A CN113127807B (en) | 2021-04-19 | 2021-04-19 | Mode5 leading pulse jitter value calculation method based on constrained least square algorithm |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113127807A true CN113127807A (en) | 2021-07-16 |
CN113127807B CN113127807B (en) | 2023-02-24 |
Family
ID=76777766
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110418588.2A Active CN113127807B (en) | 2021-04-19 | 2021-04-19 | Mode5 leading pulse jitter value calculation method based on constrained least square algorithm |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113127807B (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113938368A (en) * | 2021-10-18 | 2022-01-14 | 上海大学 | LTE-V receiving end synchronization method and system based on FPGA |
CN115098173A (en) * | 2022-06-17 | 2022-09-23 | 电子科技大学 | Dual-core AMP framework-based method for identifying friend or foe identification signals at high speed |
CN116166934A (en) * | 2023-04-25 | 2023-05-26 | 成都允高科技有限公司 | IFF signal identification method, device and medium based on cross algorithm |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4401987A (en) * | 1979-04-03 | 1983-08-30 | Sonatech, Inc. | Ranging system having reduced recognition jitter |
CN1320910A (en) * | 1998-07-23 | 2001-11-07 | 三星电子株式会社 | Method for control of writing pulse waveform of high density optical recording medium |
FR2829584A1 (en) * | 2001-09-07 | 2003-03-14 | Thales Sa | PROCESS AND DEVICE FOR GENERATING SEVERAL CHANNELS IN AN IFF TYPE SYSTEM |
CN1662971A (en) * | 2002-06-20 | 2005-08-31 | 皇家飞利浦电子股份有限公司 | Method and device for determining a set of recording pulse series parameters for optical carrier recording, and optical record carrier |
CN102983932A (en) * | 2012-11-30 | 2013-03-20 | 四川九洲空管科技有限责任公司 | Electronic interference method for identification friend or foe interrogator |
CN104820219A (en) * | 2015-05-25 | 2015-08-05 | 扬州宇安电子科技有限公司 | Active radar beacon machine and processing method thereof based on virtual target |
CN108470089A (en) * | 2018-02-12 | 2018-08-31 | 杭州电子科技大学 | A kind of complex signal delay time estimation method based on least square sample fitting |
US20190250266A1 (en) * | 2018-02-14 | 2019-08-15 | Seamatica Aerospace Ltd. | Method and system for tracking objects using passive secondary surveillance radar |
US20200371201A1 (en) * | 2019-05-20 | 2020-11-26 | Bae Systems Information And Electronic Systems Integration Inc. | Intelligent pulse jam detection for identification friend or foe (iff) systems |
CN112036074A (en) * | 2020-07-27 | 2020-12-04 | 西安电子科技大学 | Radar signal sorting method and system under high pulse density environment |
-
2021
- 2021-04-19 CN CN202110418588.2A patent/CN113127807B/en active Active
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4401987A (en) * | 1979-04-03 | 1983-08-30 | Sonatech, Inc. | Ranging system having reduced recognition jitter |
CN1320910A (en) * | 1998-07-23 | 2001-11-07 | 三星电子株式会社 | Method for control of writing pulse waveform of high density optical recording medium |
FR2829584A1 (en) * | 2001-09-07 | 2003-03-14 | Thales Sa | PROCESS AND DEVICE FOR GENERATING SEVERAL CHANNELS IN AN IFF TYPE SYSTEM |
CN1662971A (en) * | 2002-06-20 | 2005-08-31 | 皇家飞利浦电子股份有限公司 | Method and device for determining a set of recording pulse series parameters for optical carrier recording, and optical record carrier |
CN102983932A (en) * | 2012-11-30 | 2013-03-20 | 四川九洲空管科技有限责任公司 | Electronic interference method for identification friend or foe interrogator |
CN104820219A (en) * | 2015-05-25 | 2015-08-05 | 扬州宇安电子科技有限公司 | Active radar beacon machine and processing method thereof based on virtual target |
CN108470089A (en) * | 2018-02-12 | 2018-08-31 | 杭州电子科技大学 | A kind of complex signal delay time estimation method based on least square sample fitting |
US20190250266A1 (en) * | 2018-02-14 | 2019-08-15 | Seamatica Aerospace Ltd. | Method and system for tracking objects using passive secondary surveillance radar |
US20200371201A1 (en) * | 2019-05-20 | 2020-11-26 | Bae Systems Information And Electronic Systems Integration Inc. | Intelligent pulse jam detection for identification friend or foe (iff) systems |
CN112036074A (en) * | 2020-07-27 | 2020-12-04 | 西安电子科技大学 | Radar signal sorting method and system under high pulse density environment |
Non-Patent Citations (4)
Title |
---|
Y SASAKI ET.AL: "Highly efficient waveform acquisition condition in equivalent-time sampling system", 《2018 IEEE 27TH ASIAN TEST SYMPOSIUM》 * |
YOUNES AHMADI ET.AL: "Deinterleaving of Interfering Radars Signals in Identification Friend or Foe Systems", 《18TH TELECOMMUNICATIONS FORUM TELFOR 2010》 * |
吕敏: "一种Mark XIIA 模式5 信号的分选方法", 《电讯技术》 * |
王洪: "1030/1090MHz 频谱的共享与干扰问题综述", 《电讯技术》 * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113938368A (en) * | 2021-10-18 | 2022-01-14 | 上海大学 | LTE-V receiving end synchronization method and system based on FPGA |
CN113938368B (en) * | 2021-10-18 | 2023-12-12 | 上海大学 | LTE-V receiving end synchronization method and system based on FPGA |
CN115098173A (en) * | 2022-06-17 | 2022-09-23 | 电子科技大学 | Dual-core AMP framework-based method for identifying friend or foe identification signals at high speed |
CN115098173B (en) * | 2022-06-17 | 2024-04-26 | 电子科技大学 | Method for identifying friend and foe identifying signal at high speed based on dual-core AMP architecture |
CN116166934A (en) * | 2023-04-25 | 2023-05-26 | 成都允高科技有限公司 | IFF signal identification method, device and medium based on cross algorithm |
Also Published As
Publication number | Publication date |
---|---|
CN113127807B (en) | 2023-02-24 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN113127807B (en) | Mode5 leading pulse jitter value calculation method based on constrained least square algorithm | |
Bartoletti et al. | Blind selection of representative observations for sensor radar networks | |
Paul et al. | Extending joint radar-communications bounds for FMCW radar with Doppler estimation | |
Suski II et al. | Radio frequency fingerprinting commercial communication devices to enhance electronic security | |
Wang et al. | GNSS interference detection using statistical analysis in the time-frequency domain | |
Sharp et al. | Indoor TOA error measurement, modeling, and analysis | |
CN106950532B (en) | Based on cross ambiguity function compared with wave-form similarity united delay time estimation method | |
Wang et al. | GNSS jamming mitigation using adaptive-partitioned subspace projection technique | |
Khyam et al. | Multiple access chirp-based ultrasonic positioning | |
Moschevikin et al. | Investigations on passive channel impulse response of ultra wide band signals for monitoring and safety applications | |
Sen | Adaptive OFDM radar waveform design for improved micro-Doppler estimation | |
CN116068501A (en) | Method for generating anti-interference radio altimeter modulation signal | |
Colone et al. | Reference-free amplitude-based WiFi passive sensing | |
Navratil et al. | Position estimate using radio signals from terrestrial sources | |
CN106209715B (en) | A kind of amplitude modulated jamming suppressing method offseted based on time domain | |
Liang et al. | Orthogonal waveform design and performance analysis in radar sensor networks | |
Chen et al. | Passive localization for emitter with unknown LFM signal based on signal parameter estimation | |
Sun et al. | Target localization sensitivity using MIMO radar in the presence of antenna position uncertainties | |
Xia et al. | Doppler rate-of-change estimation method for BPSK signal based on spectrum phase | |
Ren et al. | Novel smart noise jamming suppression method based on smeared spectrum | |
Xia et al. | Direct tracking of co-channel moving sources with different cyclic frequencies | |
Sobhani et al. | Bayesian tracking in UWB radar sensor networks | |
Lv et al. | Frequency spot jamming against FMICW | |
Piccinni et al. | Distance Estimation Algorithm for Wireless Localization Systems Based on Lyapunov Sensitivity Theory | |
Li et al. | A non-uniform DFT-based batch acquisition method for enhanced DME (eDME) Carrier Phase: Concept, simulations, and flight test results |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |